Statistical seismology of transverse waves in the solar corona

Abstract

Context. Observations show that transverse oscillations commonly occur in solar coronal loops. The rapid damping of these waves has been attributed to resonant absorption. The oscillation characteristics carries information of the structuring of the corona. However, self-consistent seismological methods that extract information from individual oscillations are limited because there are fewer observables than unknown parameters in the model, and the problem is underdetermined. Furthermore, it has been shown that one-to-one comparisons of the observed scaling of period and damping times with wave damping theories are misleading. Aims. We aim to investigate whether seismological information can be gained from the observed scaling laws in a statistical sense. Methods. A statistical approach is used whereby scaling laws are produced by forward modelling using distributions of values for key loop cross-sectional structuring parameters. We study two types of observations: 1) transverse loops oscillations as seen mainly with TRACE and SDO and 2) running transverse waves seen with the Coronal Multichannel Polarimeter (CoMP). Results. We demonstrate that the observed period-damping time scaling law does provide information about the physical damping mechanism, if observations are collected from as wide range of periods as possible and a comparison with theory is performed in a statistical sense. The distribution of the ratio of damping time over period, i.e. the quality factor, has been derived analytically and fitted to the observations. A minimum value for the quality factor of 0.65 has been found. From this, a constraint linking the ranges of possible values for the density contrast and inhomogeneity layer thickness is obtained for transverse loop oscillations. If the layer thickness is not constrained, then the density contrast is at most equal to 3. For transverse waves seen by CoMP, it is found that the ratio of maximum to minimum values for these two parameters has to be less than 2.06; i.e., the sampled values for the layer thickness and Alfvén travel time come from a relatively narrow distribution. Conclusions. Now that more and more transverse loop oscillations have been analysed, a statistical approach to coronal seismology becomes possible. Using the observed data cloud, we have found restrictions to the loop's density contrast and inhomogeneity layer thickness. Surprisingly, for running waves, narrow distributions for loop parameters have been found.

Energy Propagation by Transverse Waves in Multiple Flux Tube Systems Using Filling Factors

“…The standing transverse waves have been successfully used to measure the coronal magnetic field (e.g., Nakariakov & Ofman 2001;Van Doorsselaere et al 2008b), density scale height (e.g., Andries et al 2005), crossfield structuring (e.g., Goossens et al 2002Goossens et al , 2008Aschwanden et al 2003) and Alfvén speed (e.g., Arregui et al 2007;Asensio Ramos & Arregui 2013). Also, since their discovery in 2007, the propagating transverse waves have been equally well exploited to measure the determining loop properties (e.g., Verth et al 2010;Goossens et al 2012b;Verwichte et al 2013).…”

Determination of the cross-field density structuring in coronal waveguides using the damping of transverse waves

“…An overview of recent seismology applications can be found in Arregui (2012) andNakariakov (2012). The increase in the number of observed events has lately enabled the application of statistical techniques to seismology diagnostics (Verwichte et al 2013;.…”

Excitation and damping of broadband kink waves in the solar corona

“…To test our proposed analysis technique we use numerical data since this has no noise. The spread in the observational data might also be a result of averaging along multiple loops along the line of sight, as considered by Verwichte et al (2013b) who used a statistical approach to produce distributions for the values of loop parameters. We shall see in the following sections that it is indeed possible to identify the damping profile from broadband signals when the data is sufficiently clean and a single loop can be considered.…”